Experienced Engineer, Data Management

Job Description

Key Responsibilities

• Architect, build, test, deploy, and support batch and real-time data pipelines and aggregation processes that deliver accurate, timely data for analytics and reporting.
• Prepare moderately complex structured and unstructured data by ingesting, parsing, profiling, wrangling, cleansing, standardizing, matching, and organizing it for downstream use.
• Implement data quality rules and controls; investigate defects, identify root causes, coordinate remediation, and monitor quality trends against agreed standards.
• Develop custom programs, reusable data assets, and platform components that address defined business intelligence, analytics, and data science needs.
• Integrate data across enterprise platforms, document source-to-consumption lineage and metadata, and support governed master and reference data.
• Automate repeatable workflows and operational controls to improve scalability, reliability, efficiency, and user experience.
• Apply responsible AI, information security, data privacy, Johnson & Johnson’s Credo, and Leadership Imperatives in day-to-day delivery and decision-making.

Qualifications

• · Bachelor’s degree or equivalent in Computer Science, Engineering, Information Systems, Statistics, Mathematics, Data Science, Economics, Finance, or a related quantitative field.
• · Minimum of 5 years of related experience in data engineering, data management, analytics, business intelligence, or a comparable technical field.
• · Hands-on experience architecting automated data flows and building production data pipelines using Python, R, or Scala and SQL, or ETL tools such as Alteryx, KNIME, or similar platforms.
• · Experience integrating enterprise data sources and evaluating data quality through profiling, validation, cleansing, standardization, monitoring, and remediation.
• · Strong analytical skills and hands-on experience working with structured and unstructured data, quantitative analysis, and data visualization.
• · Experience with enterprise data platforms and cloud technologies, including Databricks and Azure, AWS, GCP, or comparable environments.
• · Working knowledge of data modeling, metadata, lineage, semantic layers, master and reference data, and governance controls.
• · Experience using analytical or visualization tools such as Tableau, Power Apps, Power BI, Qlik, Cognos, Shiny, Dash, or Streamlit.
• · Working knowledge of automation, AI-assisted analytics, machine learning, or GenAI concepts, with the ability to apply responsible AI and sensitive-data handling requirements.
• · Strong collaboration, communication, problem-solving, and stakeholder management skills, including the ability to translate technical concepts into business value.
• · Fluency in English, written and spoken.

Preferred Skills

• · Experience with procurement data domains and source-to-settle processes, including supplier, spend, contract, category, sourcing, and purchasing data.
• · Knowledge of procurement and ERP platforms such as SAP, Ariba, VISION, eICD, Cognos, or comparable systems.
• · Experience applying AI or machine learning to data quality, stewardship, entity resolution, anomaly detection, or analytics use cases.